Similarity of Deforming Meshes Based on Spatio-temporal Segmentation

dc.contributor.authorLuo, Guoliangen_US
dc.contributor.authorCordier, Fredericen_US
dc.contributor.authorSeo, Hyewonen_US
dc.contributor.editorBenjamin Bustos and Hedi Tabia and Jean-Philippe Vandeborre and Remco Veltkampen_US
dc.date.accessioned2014-12-15T13:52:08Z
dc.date.available2014-12-15T13:52:08Z
dc.date.issued2014en_US
dc.description.abstractIn this study, we investigate a similarity metric for comparing two deforming meshes. While there have been a large body of works on computing the similarity of static shapes, similarity judgments on deforming meshes are not studied well. Our algorithm uses the degree of deformation to binarily label each triangle in deforming mesh in the spatio-temporal domain, which serves as basis for the spatio-temporal segmentation. The segmentation results are encoded in a form of evolving graph, with an aim of obtaining a compact representation of the motion of the mesh. Finally, we formulate the similarity computation as a sequence matching problem: After clustering similar graphs and assigning each of the graphs with the cluster labels, each deforming mesh is represented with a sequence of labels. Then, we apply a sequence alignment algorithm to compute the locally optimal alignment between the two cluster label sequences, and to compute the similarity metric by normalizing the alignment score. We show that similarities of animation data can be captured correctly by our approach. This may be significant, as it solves a problem that cannot be handled by current approaches.en_US
dc.description.seriesinformationEurographics Workshop on 3D Object Retrievalen_US
dc.identifier.isbn978-3-905674-58-3en_US
dc.identifier.issn1997-0463en_US
dc.identifier.urihttps://doi.org/10.2312/3dor.20141053en_US
dc.identifier.urihttps://diglib.eg.org/handle/10.2312/3dor.20141053.077-084
dc.publisherThe Eurographics Associationen_US
dc.subjectI.3.7 [Computer Graphics]en_US
dc.subjectThree Dimensional Graphics and Realismen_US
dc.subjectAnimationen_US
dc.titleSimilarity of Deforming Meshes Based on Spatio-temporal Segmentationen_US
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